Assessment of Health Risk Behaviours among Secondary School Students in Enugu, South-East, Nigeria
Bibliographic record
Abstract
INTRODUCTION: Health risk behaviours contribute to the leading causes of deaths and disability among adults and youth. OBJECTIVE: The purpose of the study was to investigate the prevalence of health risk behaviours among secondary school students in Enugu, South-East Nigeria.METHODS: This cross sectional study was conducted between May and July 2015 among 348 school students randomly selected in six secondary schools in rural and urban areas. Data was analysed using SPSS version 21, and statistical significance of association between variables was assessed using Chi-square test at p<0.05.RESULTS: Overall, 348 respondents out of 360 returned the completed questionnaires. 50.6% were females, while their mean age was 15.2 ± 5.1 years. Majority of respondents live with both parents (73.9%).Many respondents 44.5% had taken alcohol, while 13.5%, and 40.8% had smoked cigarette and had sex before respectively. Also, 59.8% had experienced one form of violence, while 37.6% of them preferred fast food junks to food prepared at home.Age, sex and class did not significantly influence participants that had taken alcohol. Also, age, sex and class did not significantly influence those that had sex in the past. However, sex significantly influenced smoking of cigarettes.CONCLUSIONS & RECOMMENDATIONS: Our results showed high percentage of health risky behaviours among secondary school students. Introduction of compulsory health education curriculum activities in schools was recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".